Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
作者提供的说明(英文原文)
Evidence-backed architecture-quality analysis for Python agent applications.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
Authorization你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
这个地址需要在请求的 header 中放入密钥,而添加连接器的菜单无法设置。请改用 Claude Code、Cursor 或 VS Code。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"uptocode": {
"command": "uvx",
"args": [
"uptocode",
"serve",
"--transport",
"stdio"
]
}
}
}在终端中运行这条命令
claude mcp add --transport http uptocode https://uptocode-mcp-1015314816960.us-central1.run.app/mcp --header 'Authorization: Bearer {UPTOCODE_API_KEY}'claude mcp add uptocode -- uvx uptocode serve --transport stdio运行前请先填写空着的值。
粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"uptocode": {
"url": "https://uptocode-mcp-1015314816960.us-central1.run.app/mcp",
"headers": {
"Authorization": "Bearer {UPTOCODE_API_KEY}"
}
}
}
}粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"uptocode": {
"command": "uvx",
"args": [
"uptocode",
"serve",
"--transport",
"stdio"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"uptocode": {
"type": "http",
"url": "https://uptocode-mcp-1015314816960.us-central1.run.app/mcp",
"headers": {
"Authorization": "Bearer {UPTOCODE_API_KEY}"
}
}
}
}粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"uptocode": {
"type": "stdio",
"command": "uvx",
"args": [
"uptocode",
"serve",
"--transport",
"stdio"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个地址需要在请求的 header 中放入密钥,而添加连接器的菜单无法设置。请改用 Claude Code、Cursor 或 VS Code。
你的选择通过 Cookie 保存在这台设备上,无需账户。
Authorization HTTP header这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
我们还没有读取这个服务器的工具列表;我们会轮流检查各个端点。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日
注册名称已通过 GitHub 账户 DDYRich72 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
尚未检查;我们会轮流检查各个端点
尚未检查;我们会轮流检查各个端点
尚未检查;我们会在检查端点时读取工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
两种方式都可以:安装在你的电脑上,或者连接云端版本。
GitHub 仓库最后更新于–,最新版本(1.0.0)于4个月前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接,所以接受远程 MCP 服务器的应用也可以使用,例如开启开发者模式的 ChatGPT。
同一分类中有:Spec Driven Development, Remote Desktop Commander, Python MCP
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Local-only Python MCP server for the Files.com API.
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
UpToCode is a design-time architecture-quality scanner for Python and TypeScript agent applications. It finds missing execution bounds, run budgets, approvals, validation, resilience controls, evals, and observability; explains the evidence; and produces an approval-driven plan for Codex without rewriting source code.
The product is deliberately narrower than a general agent-security scanner. Version 1.7 recognizes OpenAI, Anthropic, CrewAI, PydanticAI, LlamaIndex, LangGraph, conservative custom Python/TypeScript loops, and positive evidence of unbounded context growth. Static scans are local and offline. Optional GPT‑5.6 judgment remains explicit, bounded, redacted, and code-sharing gated.
The Python distribution, import package, and command are all
uptocode. Version 1.0.0
is the published baseline; this source tree is prepared as 1.10.0 for the operator-gated Batch 3 release train.
UpToCode requires Python 3.11 or newer. Install the verified 1.0 release from PyPI:
python -m pip install "uptocode==1.0.0"
uptocode --help
For repository development, use the editable test environment:
python -m pip install -e ".[test]"
uptocode --help
All ordinary tests are mocked/offline:
python -m pytest -q
python scripts/acceptance.py
The repository and package are public. No hosted credential or paid model call is required for the complete offline test build.
git clone https://github.com/DDYRich72/UpToCode.git
cd UpToCode python -m venv .venv
Activate the environment with .venv\Scripts\activate on Windows PowerShell or source .venv/bin/activate on POSIX, then run:
python -m pip install --upgrade pip
python -m pip install -e ".[test]" uptocode scan fixtures/bad_python --fail-on critical uptocode scan fixtures/bad_python --format json --output report.json uptocode review report.json --approve AA001,AA003 --reject AA012 --non-interactive uptocode plan report.json --manifest .uptocode/manifest.json --output FIXPLAN.md python scripts/acceptance.py
The first scan intentionally exits 1 because the fixture contains critical findings. The remaining commands produce a report-bound review manifest and an approved-only FIXPLAN.md; they do not edit the fixture. To inspect the local MCP surface, run uptocode serve --transport stdio --root . from an MCP client or use the JSON registration under MCP registration. python scripts/acceptance.py also launches a real stdio server, lists all ten tools, and calls check_loop offline.
The submitted-content hosted transport is deployed at https://uptocode-mcp-1015314816960.us-central1.run.app/mcp. Its bearer credential is issued separately and read from UPTOCODE_API_KEY; never commit it or enter it into the website. The immutable production revision passed readiness, unauthorized-access, AA001, tool-discovery, judgment-gate, rate-limit, and payload-free-log checks. Hosted judgment is off, no OpenAI key is attached, and verification made zero paid model calls.
uptocode scan PATH [--format terminal|json|html|github|sarif] [--output FILE]
[--judgment --send-code] [--fail-on critical|warning|info] [--include-experimental] [--share-safe] [--baseline FILE|--update-baseline FILE] [--changed-since REF] [--select RULES] [--ignore RULES] [--exclude GLOB] [--severity RULE=LEVEL] [--fail-on-analysis-warning] [--github-summary PATH] [--verbose] uptocode review REPORT [--approve IDS|--approve-all] [--reject IDS] [--reuse MANIFEST] [--non-interactive] uptocode plan REPORT --manifest MANIFEST [--output FIXPLAN.md] uptocode fix REPORT --manifest MANIFEST --runner codex|command [--command TEMPLATE] [--verify-command COMMAND] [--apply] uptocode serve --transport stdio --root PATH uptocode serve --transport streamable-http --mode hosted
Scanning, review, planning, and the default fix preview are non-mutating:
uptocode scan . --format json --output report.json
uptocode review report.json --approve AA001,AA003 --reject AA012 --non-interactive uptocode plan report.json --manifest .uptocode/manifest.json --output FIXPLAN.md uptocode fix report.json --manifest .uptocode/manifest.json --runner codex
review binds decisions to the exact report fingerprint. plan refuses a mismatched manifest and includes only approved findings. Neither command edits the scanned repository. fix is also a no-write dry-run unless --apply is supplied. The applying path requires a clean Git checkout, creates one retained uptocode/fix- branch/worktree per approved finding, invokes only the selected external runner there, verifies fingerprint absence, and never commits, merges, deletes work, or changes the invoking checkout.
Exit codes are 0 for no configured threshold breach, 1 for a finding at or above --fail-on (or a requested analysis-warning gate), and 2 for invalid configuration or an unrecoverable scan error. Experimental findings remain visible but require --include-experimental to affect --fail-on. --share-safe sanitizes JSON, HTML, or SARIF for distribution while retaining the repository revision. Baseline 2.1 reports new, aging, and resolved debt and preserves first_seen when updated. Suppressions may include owner, quoted reason, and an inclusive expires date. HTML requires --output. GitHub workflow commands escape untrusted command data and properties. SARIF 2.1.0 omits absent fields, declares default rule levels, and carries stable partial fingerprints. --github-summary PATH appends a bounded Markdown summary; when GITHUB_STEP_SUMMARY is set, the summary is appended there automatically.
repos:
Run pre-commit install, then use pre-commit run uptocode --all-files. To copy the project badge into your own README:
[](https://github.com/DDYRich72/UpToCode)
The repository ships a composite Action that installs UpToCode from the Action checkout, runs the scan, uploads SARIF with always(), and only then returns the preserved scanner exit code:
permissions:
contents: read security-events: write
steps:
version: source installs from the checked-out Action source. An exact semantic version, such as 1.0.0, installs the matching uptocode PyPI release. Set upload-sarif: "false" when code-scanning upload is not desired; otherwise the calling workflow needs security-events: write.
Example terminal output:
UpToCode scan
Coverage: 1/1 files analyzed Findings: 11 | Warnings: 0 | Redactions: 3 [CRITICAL] AA001 agent.py:21 - Unbounded agent loop [CRITICAL] AA003 agent.py:11 - Ungated destructive action
--judgment is rejected unless --send-code is also present.gpt-5.6, Pydantic Structured Outputs, store=false, a 2,000-token output ceiling, a 30-second timeout, and a six-rule call budget..gitignore files, default build/dependency/generated exclusions, .uptocode.yml, 1 MiB per-file and 4 MiB aggregate limits, binary/non-Python exclusion, and explicit suppressions are honored. Production UpToCode source is gated at zero suppressions.partial or failed judgment status and an analysis warning.No live API call is part of the offline test or acceptance suite. The submission smoke test requires a key and separate approval for paid usage.
| ID | Architecture defect | Tier | Severity | Primary guidance |
|---|---|---|---|---|
| AA001 | Unbounded agent loop | Static | critical | Agents SDK runner |
| AA002 | Missing output/run budget controls | Static | critical | OpenAI practical guide |
| AA003 | Ungated destructive action | Static + judgment | critical | Agents SDK approvals, OpenAI safety |
| AA004 | Unvalidated tool arguments | Static | critical | OpenAI function calling, Anthropic tool definitions |
| AA005 | Raw untrusted content in prompts | Judgment | critical | OpenAI safety, Anthropic guardrails |
| AA006 | Secret or narrow PII exposure | Static | critical | OpenAI safety |
| AA007 | Missing timeout, retry, or retry backoff | Static | warning | OpenAI practical guide |
| AA008 | Unjustified orchestration complexity | Judgment | warning | Anthropic effective agents, OpenAI practical guide |
| AA009 | Poor tool schema | Judgment | warning | OpenAI function calling, Anthropic tool definitions |
| AA010 | Unvalidated model output before side effect | Static + judgment | warning | OpenAI function calling, OpenAI safety |
| AA011 | No agent eval coverage | Static + judgment | warning | OpenAI evals, Google ADK evaluation |
| AA012 | No agent observability | Static | info | Agents SDK tracing |
| AA013 | Unbounded context growth | Static | warning | Anthropic effective agents, OpenAI practical guide |
| AA014 | Network MCP without authentication | Static | critical | MCP authorization, [FastMCP
只显示了开头部分;其余内容请在仓库中阅读